On the convergence of conditional gradient method for unbounded multiobjective optimization problems
Optimization and Control
2024-03-06 v1
Abstract
This paper focuses on developing a conditional gradient algorithm for multiobjective optimization problems with an unbounded feasible region. We employ the concept of recession cone to establish the well-defined nature of the algorithm. The asymptotic convergence property and the iteration-complexity bound are established under mild assumptions. Numerical examples are provided to verify the algorithmic performance.
Cite
@article{arxiv.2403.02671,
title = {On the convergence of conditional gradient method for unbounded multiobjective optimization problems},
author = {Wang Chen and Yong Zhao and Liping Tang and Xinmin Yang},
journal= {arXiv preprint arXiv:2403.02671},
year = {2024}
}